- Feedzai and Azul Systems announce first joint customer win with leading payment technology solutions provider
- Integrated solution provides the payment and ecommerce sectors with ultra-fast real-time fraud detection processing
SAN MATEO and SUNNYVALE Calif., June 24, 2015 – Feedzai, a big data science company that uses real-time, machine based learning to prevent fraud, and Azul Systems, the award-winning leader in Java runtime solutions, today announced their first joint customer win in the financial services sector following their recent commercial engagement.
The solution deployed at one of the world’s leading providers of payment technologies combines Zing®, Azul’s Java Virtual Machine (JVM) designed for systems that require consistent low latency and high scalability, and Feedzai’s Fraud Prevention That Learns™ software. When integrated, the two technologies provide the customer with a fraud prevention solution for omnichannel commerce with ultra-fast processing of big data and dramatic reductions in transactional latencies.
Feedzai Fraud Prevention That Learns™ software fuses big data and machine learning to allow analysts to predict and prevent electronic payment loss in real time based on behavioral analysis and understanding of the way consumers behave when they make financial transactions, in person, online or from mobile devices. Azul Zing provides consistent low-latency with high throughput and supports large in-memory datasets without performance penalties. It eliminates the operational interruptions and response time outliers often experienced by Java-based trading, risk and compliance applications in financial markets.
“The global financial marketplace is evolving at a rapid pace and institutions are focusing investment on technologies which provide immediate commercial advantage,” said Scott Sellers, CEO and President of Azul Systems. “Zing is a great fit for ecommerce and payment technology providers running high volume, mission critical systems – it is the only JVM designed to deliver high sustained throughput combined with consistent low latency.”
“Ultra low latencies are of paramount importance to many of our customers, which is almost impossible to achieve if you use a standard JVM,” said Nuno Sebastiao, Chief Executive Officer of Feedzai. “Fraud Prevention That Learns™ combined with Azul Zing can handle peak load demands of up to 50,000 transactions per second, which guarantees that we can deliver the best that artificially intelligent machines can offer.”
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About Azul Systems
Azul Systems, the industry’s only company exclusively focused on Java and the Java Virtual Machine (JVM), builds fully supported, certified standards-compliant Java runtime solutions that help enable the real time business. Zing is a JVM designed for enterprise Java applications and workloads that require any combination of low latency, high transaction rates, large working memory, and/or consistent response times. Zulu is Azul’s certified, freely available open source build of OpenJDK with a variety of flexible support options, available in configurations for the enterprise as well as custom and embedded systems. For additional information, visit: www.azulsystems.com.
Every day, the modern world produces petabytes of data, and Feedzai enables businesses to accurately analyze this information to keep their customers’ data and transactions safe at any place or moment in time. Feedzai’s machine learning platform transforms the management of risk and fraud into a real-time decision science to help payment providers, banks and retailers prevent fraud in omnichannel commerce. Customers use Feedzai’s Fraud Prevention That Learns™ software to predict and prevent payment loss when shopping in store, online or via mobile devices. For additional information, visit http://www.feedzai.com.